Current Source Density Estimation Enhances the Performance of Motor-Imagery Related Brain-Computer Interface
- Submitting institution
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University of Ulster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 76630004
- Type
- D - Journal article
- DOI
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10.1109/TNSRE.2017.2726779
- Title of journal
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Article number
- -
- First page
- 2461
- Volume
- 25
- Issue
- 12
- ISSN
- 1534-4320
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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A - Intelligent Systems Research Centre
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- <11> The methods presented supported a successful bid for the UK-India Education and Research Initiative in collaboration with IIT Kanpur (Advancing MEG-based Brain-Computer Interface Supported Upper Limb Post-Stroke Rehabilitation, £144,546) and have been deployed in a brain-computer interface to control an exoskeleton which has been trialed by stroke survivors (reported in impact case study 2 (ICS2) returned in this REF2021).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -